sb-ai-lab/LightAutoML

Health v2 · maintenance only

Adoption not part of the score

1472 stars · 70 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

LightAutoML (LAMA) is a Python framework for automatic machine learning model creation (AutoML) supporting tabular, time series, image, and text data. It offers ready-to-use presets that build models in a few lines of code as well as customizable pipeline blocks for advanced users.

Use cases

• automatically train models on tabular data with a few lines of code
• solve binary classification, multiclass classification, and regression tasks
• build custom AutoML pipelines from reusable blocks
• handle mixed data types including text, images, and time series
• create strong Kaggle competition baselines quickly
• generate interpretable white-box models

When to choose

• you want automated feature engineering, model selection, and ensembling without manual tuning
• you need fast AutoML for tabular datasets in Python
• you want a customizable AutoML framework with preset and framework modes
• you need support for text and image features alongside tabular data

When to avoid

• you need full manual control over every modeling step
• you require deep learning architectures beyond what presets provide
• you work outside Python or need distributed large-scale training out of the box

Facets

library · maturity active

machine-learning data-science nlp machine-learning data-science artificial-intelligence python cross-platform automl auto-ml tabular-data time-series kaggle binary-classification regression multiclass-classification

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markdown · JSON · MCP: product_card(name="sb-ai-lab/LightAutoML")